Project Summary Of the non-coding genome that makes up about 98% of the human genome and plays a key role in the regulation of gene expression, about half consists of retrotransposons, a large group of transposable elements (TEs) that can ?copy and paste? their own DNA in the host genome. Variations in DNA sequence and RNA expression of regulatory elements, rather than of protein-coding genes, act as major risk factors in neuropsychiatric disorders, like schizophrenia (SZ). While evidence is emerging that RNA-mediated epigenetic regulation may rewire gene-networks, we still lack a detailed knowledge of these processes in the neural genome. HERVs are the most represented elements of the Long Terminal Repeat class (LTR) of TEs, and make up 8% of the nuclear DNA. Intact HERVs maintain the structure of a retrovirus, but the vast majority are truncated or just Solo-LTRs. Yet, HERVs can be functionally expressed, acting primarily as enhancers or promoters of neighboring genes in various tissues, as in the brain, with a putative functional role in diseases, like SZ. However, almost all HERVs studies looked at the expression of a given sub-family, like up-regulation of HERV- K expression in SZ, rather than pinpointing the exact genomic instance of a specific HERV (eg HERVK-1), limiting our understanding of their functional role. We developed a bioinformatics pipeline to improve the assessment from RNA-sequencing data of individual HERV transcriptional profiles at their chromosomal location and further confirmed our in silico findings with an independent experimental validation. Building on our expertise in developing methods and algorithms for detecting and analyzing TEs from sequencing data, we propose to map HERV transcripts to their specific chromosomal locations and quantify their expression in the CommonMind dataset (n = 600), the largest publicly available post-mortem Dorsal-Lateral Prefrontal Cortex (DLPFC) dataset for SZ. We will test whether their expression is altered in SZ (Aim 1); whether HERV-associated SNPs are functional eQTL in SZ (i.e. HERV-eQTL) (Aim2); and, finally, whether differentially expressed HERVs are regulatory elements by assessing their interaction with protein-coding target genes using Chromosome Conformation Capture on Chip (4C) (Aim 3). Following the identification of differential expression of HERVs in brain tissues, we are now prepared to characterize the molecular mechanisms by which HERVs impact on the neural genome and detect how their dysregulation contribute to Schizophrenia. Identification of these mechanisms will make a major contribution to our understanding of how epigenetics can reprogram the neural genome, opening up new avenues for developing pathogenic-targeted drug treatments in schizophrenia.